Immunoexpression profile of hypoxia-inducible factor (HIF) targets in potentially malignant and malignant oral lesions: a pilot study

Abstract Oral potentially malignant disorders (OPMD) are associated with an increased risk of oral squamous cell carcinoma (OSCC). OSCC has an aggressive profile and is the most prevalent among different head and neck malignancies. Most OSCC patients are diagnosed with advanced stage tumors and have a poor prognosis. Cancer cells are able to reprogram their metabolism, even in the presence of oxygen, enhancing the conversion of glucose to lactate via the glycolytic pathway, a phenomenon mainly regulated by hypoxia-inducible factor (HIF) signaling. Thus, several glycometabolism-related biomarkers are upregulated. Objectives This study aimed to evaluate the immunoexpression of the HIF targets GLUT1, GLUT3, HK2, PFKL, PKM2, pPDH, LDHA, MCT4, and CAIX in OPMD and OSCC samples, in order to identify potential correlations between biomarkers’ immunoexpression, clinicopathological features, and prognostic parameters. Methodology OSCC and OPMD samples from 21 and 34 patients (respectively) were retrospectively collected and stained for the different biomarkers by immunohistochemistry. Results CAIX and MCT4 expressions were significantly higher in OSCC samples when compared with OPMD samples, while the rest were also expressed by OPMD. GLUT3 and PKM2 alone, and the concomitant expression of more than four glycometabolism-related biomarkers were significantly correlated with the presence of dysplasia in OPMD. When considering OSCC cases, a trend toward increased expression of biomarkers and poor clinicopathological features was observed, and the differences regarding HK2, PFKL, LDHA and MCT4 expression were significant. Moreover, HK2 and CAIX were correlated with low survival rates. GLUT1 and GLUT3 were significantly associated with poor outcome when their expression was observed in the hypoxic region of malignant lesions. Conclusion OPMD and OSCC cells overexpress glycolysis-related proteins, which is associated with aggressive features and poor patient outcome. Further research is needed to deeply understand the glycolic phenotype in the process of oral carcinogenesis.


Introduction
Oral cancer (OC), which includes lip and oral cavity malignancies, is the most prevalent among different subtypes of head and neck cancers (HNC). The incidence rate is progressively increasing: 377,713 new cases and 177,757 OC-related deaths were estimated worldwide in 2020. OC occurs mainly in regions of South and Central Asia and Melanesia, with a high prevalence in men. 1 In terms of etiology, both hereditary -family history of cancer and personal defective immune system -and non-hereditary factors -tobacco, alcohol, and HPV virus (high-risk HPV) -play an important role in oral carcinogenesis. 2 Oral potentially malignant disorders (OPMD), such as oral lichen planus (OLP) and leukoplakia, are also associated with an increased risk of OC, especially lesions with high-grade dysplasia. Most OPMD are asymptomatic in the early stages of their evolution, which makes knowledge of their clinical aspects essential for a timely diagnosis and surveillance. 3 Oral squamous cell carcinoma (OSCC) is the predominant histological type of OC. The successful treatment strategy for OSCC patients at an early stage is surgery followed by radiotherapy. In advanced stages, surgery is combined with cisplatin-based chemotherapy, which increases survival rates. Despite advancements in the treatment of OSCC, this malignancy is not usually detected in the early stages, and more than half of patients succumb to the disease within five years of diagnosis. Moreover, conventional treatments have significant medical costs and associated comorbidities. 2 Therefore, it is necessary to search for new diagnostic and prognostic biomarkers that can improve patients' outcome and quality of life.
Cancer cells, regardless of oxygen availability, use much higher glucose levels than their non-cancerous counterparts, with further fermentation of pyruvate to lactate rather than oxidation in the mitochondria. This phenomenon called the Warburg effect upregulates the expression of glycolytic enzymes and other glycometabolism-related proteins. 4 In OSCC, similarly to other types of cancer, the activated HIF-1 (hypoxiainducible factor 1) signaling pathway seems to be the main regulator of the Warburg phenotype. 5 In this pathway, HIF-1α increases the expression of glucose transporters (GLUT), namely GLUT1 and GLUT3, which results in increased glucose uptake. During glucose metabolism, HIF-1α also promotes the conversion of glucose to pyruvate by increasing the expression of glycolytic enzymes such as hexokinase 2 (HK2; which catalyzes the conversion of glucose to glucose-6-phosphate II), phosphofructokinase (PFK; which accelerates the conversion of fructose-6-phosphate to fructose-1,6-bisphosphate, mainly the L type), and pyruvate kinase isoform M2 (PKM2; which catalyzes the conversion of phosphoenolpyruvate to pyruvate). 6 Electron flux through oxidative phosphorylation is inhibited by pyruvate dehydrogenase kinase (PDK), a negative regulator of pyruvate dehydrogenase (PDH; which catalyzes the conversion of pyruvate to acetyl-CoA), and lactate dehydrogenase A (LDHA; which catalyzes the conversion of pyruvate to lactate), both under HIF-1 signaling. 7 Table S1.
Staining intensity was graded as 0 (negative), 1 (weak), 2 (moderate), or 3 (strong). Extension and intensity scores were summed to obtain the final score and clustered as negative (score 0-2 or 0-3) and positive (score 3-6 or 4-6), depending on the biomarker. The final scores that provided the most informative results regarding clinicopathological and prognostic implications for each studied biomarker were considered. Protein localization (cytoplasm, nucleus, and/or cell membrane) was also assessed.   Immunoexpression of Glycometabolism-Related Biomarkers in OPMD and OSCC As previously mentioned, we considered the scores that allowed us to obtain the most informative results as the final staining scores for each biomarker. Thus, positivity was considered as >3 for GLUT1, GLUT3, PFKL, pPDH, LDHA, MCT4, and CAIX, and >4 for PKM2 and HK2. Significant differences were obtained when comparing the immunoexpression frequencies of CAIX (p<0.001) and MCT4 (p=0.011) in OPMD (uniform assessment of protein expression) and OSCC lesions (assessment of protein expression in normoxic regions), with a higher percentage of positive cases for these biomarkers in OSCC samples. An inverse correlation was observed when GLUT3 (p=0.033) and PFKL (p=0.023) expression frequencies were analyzed. Detailed information on the frequencies of biomarker immunoexpression is shown in Table 3.   Table   4.
Regarding OPMD, all patients with leukoplakia with high-grade dysplasia (3/3)  Kaplan-Meier survival analysis of OSCC patients regarding biomarker immunoexpression revealed that high HK2 expression was significantly correlated with worse DFS (p=0.007; Figure 4A) and nearly significantly associated with worse OS (p=0.060; Figure 4B). Moreover, a clear separation regarding OS rates was obtained between the negative and positive  CAIX groups (p=0.071; Figure 4C) and between the low and high GP groups (p=0.156; Figure 4D     GLUT1 and GLUT3 immunoexpression did not associate with the clinicopathological parameters, but significant associations were observed between positivity of these biomarkers in the hypoxic region of tumors and a low overall survival rate (p=0.044 and p=0.006, respectively; Figures 6A and 6B). HK2 expression was significantly associated with poor disease-free survival (p=0.009; Figure 6C). Detailed results are presented in Tables S9 and S10 (Supplementary Data).

Discussion
In this study, we sought to evaluate the expression of glycometabolism-related biomarkers in the process of oral carcinogenesis, specifically from OPMD to malignancy. The expression pattern of some glycometabolism-related proteins in oral lesions has been evaluated, 10 although those studies have mainly focused on OSCC rather than potentially malignant conditions. Thus, we conducted a pilot study with 34 OPMD and 21 OSCC cases. The low number of cases within each group does not allow simple conclusions to be drawn regarding the correlation between clinicopathological parameters and prognosis. Even so, the coexistence of dysplasia in oral leukoplakia lesions for GLUT3 and PFKL, while no differences were observed for the remaining biomarkers. Regarding the discrimination between hypoxic and normoxic regions, a significant immunoexpression concordance was obtained for most biomarkers, except for GLUT1 and GLUT3. As previously mentioned, the activated HIF-1 signaling pathway seems to be the main regulator of hyperglycolytic metabolism in OSCC, 5 but such a phenotype may also be activated by stimuli  Similarly to GLUT1, GLUT3 mediates glucose uptake and its upregulation has also been reported in numerous types of cancer. 16 In the study by Zhou, et al. 21 (2008), GLUT3 gene expression in HNC was significantly higher when compared with non-malignant cases, and this was correlated with the occurrence of lymph node metastasis. In another study, GLUT3 expression was associated with the clinical stage of OSCC and low DFS among patients. 20 In this study, GLUT3 had a restricted expression in OPMD and malignant lesions. Even so, and similarly to the results regarding GLUT1, although no major involvement of GLUT3 was evident in oral carcinogenesis and no association was found among clinical data, GLUT3 expression in the hypoxic region of cancer sections was significantly associated with a poor overall outcome. It is known that chronic hypoxia fluctuates with stages of normoxia recovery due to neovascularization and metastasis, which leads to increased metabolic activity and aggressiveness of cancer cells. 22 This shows the importance of evaluating biomarker expression in a heterogeneous approach in order to assess the clinical and/or prognostic value, as well as the functional aspects of the metabolic heterogeneity intrinsic to the different regions of the tumor mass.
HK2 is the first rate-limiting enzyme in the glycolysis pathway, and is upregulated in multiple types of cancer. 23 HK2 expression in OC has been reported, 24 but we found no study on OPMD. Grimm, et al. 24 (2014) showed the key role of HK2 in oral carcinogenesis, as its expression increased from normal mucosa to simple hyperplasia, squamous intraepithelial neoplasia, and OSCC tissues, where it correlated with poor survival of OSCC patients. In our study, HK2 expression was lower in OSCC samples than in OPMD samples. Interestingly, for patients with OPMD, HK2 expression was mostly seen in women. HK2 was the most informative biomarker for OSCC patients and our results showed a significant association between HK2 positivity and advanced age, large tumors, and poor prognosis.
PFKL is an important enzyme that controls the glycolytic flux and the only phosphofructokinase 1 isoform whose expression is directly affected by  To the best of our knowledge, no studies on PFKL expression in OPMD or OSCC have been reported. In esophageal cancer, high PFKL expression was associated with advanced stage tumors and poor patient survival. 26 In our study, and similarly to HK2 expression, PFKL expression was higher in OPMD than in OSCC lesions. The few (three cases) cancer sections positive for PFKL were large advanced-stage high-grade tumors.
The glycolytic protein PKM2 is another HIF-1α target that favors cancer cell survival and invasion by aerobic metabolism. 27 PKM2 expression has been reported to be significantly associated with OC progression and poor prognosis in OSCC patients, and also enhances VEGF-A expression (a direct target of HIF-1α with a major role in tumor angiogenesis). 28 In our study, PMK2 expression in both OPMD and OSCC sections was low, but a higher expression was observed in OPMD with concomitant high-grade dysplasia, as well as in advanced-stage high-graded OSCC samples.  showed a diagnostic value in the study by Pérez-Sayáns, et al. 42 (2015) due to its high specificity in identifying dysplastic lesions in premalignant conditions. This was not observed in our study. In fact, CAIX was clearly overexpressed in malignant tissues when compared with OPMD, and nearly predicted a worse outcome. However, it was not possible to distinguish CAIX expression between normoxic and hypoxic regions.
The integrative analysis of the immunolabelling results allowed us to observe expression patterns.
A highly glycolytic phenotype, i.e., the concomitant positivity of four or more biomarkers, increasingly occurred with a simultaneous increase in the malignant potential of OPMD, from OLP to leukoplakia with highgrade dysplasia. Oral dysplasia carries a 12.1% risk of progression to cancer, 43 which shows the importance of developing progression-predictive models and potential targets for early therapeutic intervention. In conclusion, this study showed that oral cancer cells overexpress glycolysis-related proteins and this associates with aggressive features, which supports a hyperglycolytic phenotype in this type of cancer.
We highlight the potential of HK2 as a prognostic biomarker. We also support that it might be useful to look for GLUT1 and GLUT3 immunoexpression in the hypoxic region of OSCC sections, as they seem to have prognostic value in this tumor section.